As data processing systems continue to grow in complexity, traditional tools used in the development, design and debug of such systems become increasingly impractical to use. For example, in the development and design of personal computers, an engineer could use a logic analyzer and oscilloscope to assist in locating errors in hardware and software. As the software running on these data processing systems became more complex, tools such as in-circuit emulators were developed, whereby the instruction flow of a central processing unit (CPU) could be captured and analyzed. These types of tools still require a large amount of human intervention and human analysis to assist in problem determination.
Various types of software tools have been introduced in the marketplace to assist in monitoring a data processing system, such as the System Performance Monitor/2 from IBM. This tool provides a graphical interface to visual depict various aspects of a data processing system, and greatly reduces the amount of time required to analyze the operation of a data processing system. Although these systems provide a substantial improvement over previous methods for monitoring and analyzing a data processing system, there are still certain deficiencies. First, they are geared towards hardware resources in a data processing system, and do not fully address the ability to monitor software processes or applications. Secondly, the flexibility and granularity provided are limited. Further, performance data is merely output to a user display device, and thus does not provide full flexibility in analyzing the data being captured.
Network monitoring tools such as IBM NetView/6000 (TM) programs are concerned primarily with supervision and corrective action aiming at keeping the network resources available and accessible. Resource availability is the concern of such tools, rather than resource utilization. For example, IBM NetView/6000 tracks the amount of free space of a disk.
There is a need to provide a data processing system performance tool that is flexible and easy to use, that can monitor hardware as well as software events and process activities, that can capture data (e.g. read sampled data) for subsequent retrieval and analysis, and that provides other facilities to further analyze and categorize such captured data.